Quantization for Robust Distributed Coding

A distributed source coding approach is proposed for robust data communications in sensor networks. When sensor measurements are quantized, possible correlations between the measurements can be exploited to reduce the overall rate of communication required to report these measurements. Robust distri...

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Bibliographic Details
Published in:International journal of distributed sensor networks Vol. 2016; no. 5; p. 6308410
Main Authors: Wu, Xiaolin, Bais, Abdul, Sarshar, Nima
Format: Journal Article
Language:English
Published: London, England Hindawi Publishing Corporation 01.01.2016
SAGE Publications
Sage Publications Ltd. (UK)
John Wiley & Sons, Inc
Wiley
Subjects:
Algorithms
Applied research
Codes
Coding
Coding theory
Communication
Descriptions
Design
Distortion
Distributed computing
Gaussian
Networks
Quantization
Scalars
Sensors
Wireless sensor networks
ISSN:1550-1329, 1550-1477, 1550-1477
Online Access:Get full text
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Summary:A distributed source coding approach is proposed for robust data communications in sensor networks. When sensor measurements are quantized, possible correlations between the measurements can be exploited to reduce the overall rate of communication required to report these measurements. Robust distributed source coding (RDSC) approaches differentiate themselves from other works in that the reconstruction error of all sources will not exceed a given upper bound, even if only a subset of the multiple descriptions of the distributed source code are received. We deal with practical aspects of RDSC in the context of scalar quantization of two correlated sources. As a benchmark to evaluate the performance of the proposed scheme, we derive theoretically achievable distortion-rate performances of an RDSC for two jointly Gaussian sources by applying known results on the classical multiple description source coding.
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ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2016/6308410